Lu Qiuhong, Lu Shunzu, Wang Xue, Huang Yanlan, Liu Jie, Liang Zhijian
Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, PR China; Department of Mental Health, The First Affiliated Hospital of Guangxi Medical University, Nanning, PR China.
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, PR China.
Neuroimage Clin. 2025;45:103743. doi: 10.1016/j.nicl.2025.103743. Epub 2025 Jan 27.
This study investigated changes in gray matter volume (GMV), white matter microstructure, and spontaneous brain activity in post-stroke depression (PSD) using multiple MRI techniques, including neurite orientation dispersion and density imaging (NODDI). Changes in GMV, neurite density index (NDI), orientation dispersion index (ODI), fraction of isotropic water (ISO), diffusion tensor imaging (DTI) parameters, and the amplitude of frequency fluctuations (ALFF) were assessed between PSD (n = 20), post-stroke without depression (n = 20), and normal control (n = 20) groups. Receiver operating characteristic (ROC) curve analysis was performed to test the classification performance of the variant parameters of each MRI modality, each single MRI modality and multiple MRI modality. Compared to patients with post-stroke without depression (non-PSD), those with PSD showed increased ODI and ISO in the widespread white matter, as well as increased ALFF in the left pallidum. No significant differences in the GMV or DTI parameters were observed between the two groups. Furthermore, the ODI of the right superior longitudinal fasciculus and NODDI showed the best classification performance for PSD at their respective comparison level (the areas under the ROC curves (AUC) = 0.917(0.000), 0.933(0.000)). The model of NODDI-derived parameters combined with non-diffusion MRI modality parameters (i.e., GMV and ALFF) showed better diagnostic performance than that of DTI-derived parameters. These findings suggest that PSD is associated with structural and functional abnormalities that may contribute to depressive symptoms. Additionally, NODDI showed its advantages in the description of structural alterations in emotion-related white matter pathways and classification performance in PSD.
本研究采用多种磁共振成像（MRI）技术，包括神经突方向离散度与密度成像（NODDI），调查了中风后抑郁症（PSD）患者的灰质体积（GMV）、白质微观结构及大脑自发活动的变化。评估了PSD组（n = 20）、非中风后抑郁症组（n = 20）和正常对照组（n = 20）之间GMV、神经突密度指数（NDI）、方向离散度指数（ODI）、各向同性水分数（ISO）、扩散张量成像（DTI）参数以及频率波动幅度（ALFF）的变化。进行了受试者工作特征（ROC）曲线分析，以测试每种MRI模态的变异参数、每种单一MRI模态和多种MRI模态的分类性能。与非中风后抑郁症（非PSD）患者相比，PSD患者在广泛的白质中ODI和ISO增加，左侧苍白球的ALFF也增加。两组之间在GMV或DTI参数方面未观察到显著差异。此外，右侧上纵束的ODI和NODDI在各自的比较水平上对PSD表现出最佳的分类性能（ROC曲线下面积（AUC）= 0.917(0.000)，0.933(0.000)）。由NODDI衍生参数与非扩散MRI模态参数（即GMV和ALFF）组合而成的模型显示出比DTI衍生参数更好的诊断性能。这些发现表明，PSD与可能导致抑郁症状的结构和功能异常有关。此外，NODDI在描述与情绪相关的白质通路的结构改变以及PSD的分类性能方面显示出其优势。
